Effects of Milk Fever, Ketosis, and Lameness on Milk Yield in Dairy Cows

Size: px
Start display at page:

Download "Effects of Milk Fever, Ketosis, and Lameness on Milk Yield in Dairy Cows"

Transcription

1 Effects of Milk Fever, Ketosis, and Lameness on Milk Yield in Dairy Cows P. J. RAJALA-SCHULTZ, *, Y. T. GRÖHN,* and C. E. McCULLOCH *Section of Epidemiology, Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY Department of Clinical Veterinary Sciences, Faculty of Veterinary Medicine, PO Box 57, FIN Helsinki University, Finland Biometrics Unit, Department of Statistical Science, Cornell University, Ithaca, NY Received July 17, Accepted October 20, ABSTRACT The effects of milk fever, ketosis, and lameness were studied using data from 23,416 Finnish Ayrshire cows that calved in 1993 and were followed for one lactation (i.e., until culling or the next calving). Monthly test day milk yields were treated as repeated measurements within a cow in a mixed model analysis. Disease index variables were created to relate the timing of a disease to the measures of test day milk. Statistical models for each parity and disease included fixed effects of calving season, stage of lactation, and disease index. An autoregressive correlation structure was used to model the association among the repeated measurements. The milk yield of cows contracting milk fever was affected for a period of 4 to 6 wk after calving; the loss ranged from 1.1 to 2.9 kg/d, depending on parity and the time elapsed after milk fever diagnosis. Despite the loss, cows with milk fever produced 1.1 to 1.7 kg more milk/d than did healthy cows. Milk yield started to decline 2 to 4 wk before the diagnosis of ketosis and continued to decline for a varying time period after it. The daily milk loss was greatest within the 2 wk after the diagnosis, varying from 3.0 to 5.3 kg/d, depending on parity. Cows in parity 4 or higher were most severely affected by ketosis; the average total loss per cow was kg. Lameness also affected milk yield; milk loss of cows diagnosed with foot and leg disorders varied between 1.5 and 2.8 kg/d during the first 2 wk after the diagnosis. ( Key words: metabolic diseases, milk yield, repeated measures, mixed model analysis) INTRODUCTION Milk fever and ketosis are metabolic diseases of dairy cows that usually occur at the time of calving or early in lactation, respectively. Lameness, however, can occur at any time during the lactation. The literature gives conflicting results on the effects of these diseases on milk yield. Dohoo and Martin ( 5 ) reported that clinical ketosis and foot and leg disorders have a beneficial effect on milk yield and subclinical ketosis have a detrimental effect. Detilleux et al. ( 4 ) found milk yield to be affected by ketosis, but, despite that, the ketotic cows yielded more than their healthy herdmates. Many studies (5, 10, 13) have not found any association between milk fever and milk yield. Several statistical approaches have been used to evaluate milk losses caused by diseases. Some of the discrepancies found in the literature with regard to the effects of diseases on milk yield are likely to result from differing statistical methods and different measures of milk yield used. The purpose of this study was to estimate the effects of milk fever, ketosis, and lameness on milk yield in Finnish Ayrshire cows using monthly test day milk measures in a mixed model analysis. Data MATERIALS AND METHODS The data for this study were from 23,416 Finnish Ayrshire dairy cows that calved during 1993 and were followed until the next calving or culling. The cows were in herds that belonged to the milk registry and the national dairy cow health recording system. These data are a subset of a larger study population of 39,727 Finnish Ayrshire cows, which has been described earlier (11). The veterinary diagnoses of milk fever, ketosis, and lameness were used for this study. Finnish farmers do not have access to veterinary drugs without supervision of a veterinarian, and so virtually all diseases were diagnosed and treated by a veterinarian during farm visits. Diagnoses were made according to ordinary clinical methods under normal field conditions J Dairy Sci 82:

2 EFFECTS OF METABOLIC DISEASES ON MILK YIELD 289 Only the first occurrence of disease was considered in this study. Calving dates, disease dates, and dates for monthly test day milk sampling were available. Disease occurrences were expressed as lactational incidence risks ( 8 ) and were calculated by dividing the number of cows with a particular disease by the total number of cows at risk; disease occurrences are presented as percentages. Monthly test day milk yields, taken at approximately 30-d intervals, were used to study the effects of milk fever, ketosis, and lameness on milk yield. The lactation was divided into 17 stages: milk records taken within 60 d after calving were grouped by 10-d intervals, records from 61 to 180 d were grouped into 20-d intervals, and records from 181 d and later formed 30-d intervals. Only test day milk yields until 330 d after calving were considered. Parity had four levels: 1, 2, 3, and 4 or higher. Four calving seasons were defined by 3-mo intervals: winter, December to February; spring, March to May; summer, June to August; and fall, September to November. Milk fever. Only cows with no diseases during the study lactation (n = 20,983) and such cows with milk fever but no other diseases before and within 4 wk after milk fever diagnosis (n = 1,259) were included in the analyses. Only cows in parities 2, 3, and 4 or higher were considered. To relate the test day milk yields to the time of disease diagnosis, a disease index variable was created for each test day milk yield in order to study the effects of milk fever on milk yield. Two different ways of estimating the milk loss were tested: 1) the milk yield of the healthy cows and 2) the yield of the milk fever cows more than 8 wk after the diagnosis. The milk fever index variable, when the cow s own yield later in lactation was the reference, was defined as follows: 1 = cow was healthy (i.e., had not been diagnosed with any disease during the lactation), 2 = test day yields collected within 14 d after the diagnosis, 3 = test day yields collected between 15 and 28 d after the diagnosis, 4 = test day yields collected between 29 and 42 d after the diagnosis, 5 = test day yields collected between 43 and 56 d after the diagnosis, and 6 = test day milk yields collected more than 56 d after the milk fever diagnosis (the reference level). Ketosis. Only cows with no diseases during the study lactation ( n = 20,983) and cows with ketosis but no other diseases during the entire study lactation (n = 719) were included in the analyses. In these analyses, the milk yield level prior to disease onset (more than 4 wk before the diagnosis of the disease) of the ketotic cows was used as the reference level. The ketosis index was defined as follows: 1 = cow was healthy (i.e., had not been diagnosed with any disease during the entire lactation), 2 = test day yields collected between 15 and 28 d before the diagnosis, 3 = test day milk yields collected within 14 d before the diagnosis, 4 = test day yields collected within 14 d after the diagnosis, 5 = test day yields collected between 15 and 28 d after the diagnosis, 6 = test day yields collected between 29 and 42 d after the diagnosis, 7 = test day yields collected later than 42 d after the diagnosis, and 8 = test day milk yields collected more than 28 d before the ketosis diagnosis (the reference level). Lameness. Only cows with no diseases ( n = 20,983) and cows with foot and leg disorders but no other diseases within 4 wk before and after the lameness diagnosis ( n = 455) were included in the analyses. To differentiate between cows with and without foot and leg disorders, a lameness index variable was created for each test day milk yield in order to study the effects of lameness on milk yield. The variable was defined as follows: 1 = cow was healthy (i.e., had not been diagnosed with any disease during the lactation), 2 = test day yields collected between 15 and 28 d before the diagnosis, 3 = test day milk yields collected within 14 d before the diagnosis, 4 = test day yields collected within 14 d after the diagnosis, 5 = test day yields collected between 15 and 28 d after the diagnosis, 6 = test day yields collected between 29 and 42 d after the diagnosis, 7 = test day yields collected later than 42 d after the diagnosis, and 8 = test day milk yields collected more than 28 d before the diagnosis (the reference level). Statistical Analysis Repeated measurements were present in both space and time. Cows within the same herd were clustered in space, and repeated measurements of daily milk yields of the same cow were correlated in time. What makes the repeated measures analysis distinct from simple linear models is the covariance structure of the observed data. In a typical experiment utilizing repeated measures, two measurements taken at adjacent times are typically more highly correlated than two measurements taken several time points apart (9). One type of statistical analysis that can be used for repeated measures is based on the mixed model with a special parametric structure for the covariance matrices. This type of methodology has been computationally feasible only in recent years and is applied in PROC MIXED of SAS (9), typically using the REPEATED statement. This procedure was used for

3 290 RAJALA ET AL. these data with the monthly test day milk yields as the outcome variable. A cow usually has approximately 10 monthly test day milk yields recorded during a lactation. Because milk yield measurements from the same lactation for a cow are correlated, it is important to account for this correlation in estimating the effects of disease on milk yield. In our previous study (12), we compared three commonly used correlation structures (simple, compound symmetry, and first-order autoregressive) and found the first-order autoregressive correlation structure to provide the best fit to these data, based on Akaike s information criterion and Schwartz s Baysian criterion. In PROC MIXED, the standard linear model is generalized to form a mixed model: y = Xb + Zg + e with Var(g) = G and Var(e) = R, so that Var(y) = ZGZ + R, where y = vector of test day milk yields, b = vector of fixed effects, g = random herd effects, and e = vector of random errors. A correlation pattern can be modeled in PROC MIXED in two ways, by introducing a correlation pattern in the random effects g through a nonidentity matrix G or by an R matrix so that it equals s 2 multiplied by some nonidentity matrix. The effects of milk fever, ketosis, and lameness on test day milk yields were studied separately for each parity (i.e., parities 1, 2, 3, and 4 or higher). For milk fever, the effects were studied also for parities 2 or higher together (pooled data). Calving season, stage of lactation, and disease variables were fixed effects in each model. RESULTS AND DISCUSSION The lactational incidence risks (LIR) of milk fever, ketosis, and lameness and the number of cows with these disorders are presented in Table 1. Because the lactational incidence risks of milk fever among parity 1 cows was so low, data on these cows were excluded from the analysis. To avoid the confounding effect of any other disease, only those cows with milk fever and no other diseases before or within 4 wk after the milk fever diagnosis were included in the analysis, even though some information was lost by excluding those other records. For the ketosis analysis, only cows diagnosed with ketosis and no other diseases during the entire lactation were included to avoid the confounding effect of any other diseases. Also, only cows diagnosed with foot and leg disorders that did not have any other diseases within 4 wk before or after the diagnosis were included in the study. Calving season was a very significant factor in each model for all of the diseases. Cows calving during the fall were the highest producers of milk, and cows calving in spring and summer produced significantly less milk. In most models, cows calving in winter did not significantly ( P > 0.05) differ from cows calving in fall. Milk Fever When the yield of cows with milk fever was compared with that of the healthy cows, milk fever did not have a clear milk-reducing effect in our data. On the contrary, the results suggested that cows contracting milk fever were higher yielding cows. At 2 to 4 wk after onset of the disease, cows in parities 2 or higher (the pooled data) on average yielded 0.9 kg more milk/d; during the next 2 wk, they yielded 1.2 kg more milk/d, and, during the remainder of lactation, they yielded 1.6 kg more milk/d than healthy cows (results not shown). Therefore, the milk yield of the cows with milk fever more than 8 wk after the diagnosis was chosen as the comparison level. Milk yield at this point gives an indication of the yield potential of the cow and what yield would have been from the beginning of lactation had she not contracted milk fever. TABLE 1. Lactational incidence risks (percentage) of milk fever, 1 ketosis, 2 and lameness 3 and the number of cases of each disease by parity for 23,416 Finnish Ayrshire cows that calved in 1993 and were followed for one lactation (until the next calving or culling). Disease Parity 1 Parity 2 Parity 3 Parity 4+ Overall (%) (no.) (%) (no.) (%) (no.) (%) (no.) (%) (no.) Milk fever Ketosis Lameness Cows with milk fever and no other diseases before and 4 wk after the diagnosis. 2Cows with ketosis and no other diseases during the entire lactation. 3Cows with foot and leg disorders and no other diseases within 4 wk before and 4 wk after the lameness diagnosis.

4 EFFECTS OF METABOLIC DISEASES ON MILK YIELD 291 TABLE 2. Effects of milk fever on milk yield (kilograms) by parity for 22,242 Finnish Ayrshire cows that calved in 1993 and were followed for one lactation. 1 1Yield of the cows with milk fever more than 8 wk after the diagnosis was used as the reference level. 2Period when the test day milk sample was collected with respect to the diagnosis of the disease (AD = after diagnosis). 3Total loss is the sum of statistically significant daily losses multiplied by the number of days (i.e., 14 d) in each period. *P **P ***P Parity 2 Parity 2 Parity 3 Parity 4+ Effect 2 Estimate SE Estimate SE Estimate SE Estimate SE 0 14 d AD 1.8*** * *** *** d AD 1.1*** ** *** d AD 0.5** ** d AD Healthy 1.6*** *** *** 0.2 Total loss Table 2 presents the results when the cow s own yield was used as the reference level. During the first 2 wk after the diagnosis, cows with milk fever in parities 2 or higher (the pooled data) yielded 1.8 kg less milk/d than they did later in lactation. During the following 2 wk, the loss was 1.1 kg/d, and, during the next 2 wk, it was 0.5 kg/d (Table 2). In general, healthy cows yielded 1.6 kg/d less than cows that contracted milk fever. Cows with milk fever in parity 2 yielded 2.7 kg less milk/d during the first 2 wk than later in the lactation. In parity 3, the losses from milk fever during the three 2-wk periods after calving were 2.9, 1.6, and 1.2 kg/d, chronologically. The oldest cows lost 1.4 kg/d during the first 2 wk after the diagnosis and lost 1.0 kg/d during the following 2 wk. The healthy cows produced 1.1 to 1.7 kg less milk/d than did cows with milk fever later in lactation, depending on parity (Table 2). Increased milk yield has been found to be a risk factor for milk fever in several studies (1, 2, 6, 7, 11). However, results found in the literature state that milk fever is not associated with milk loss; Rowlands and Lucey (13) and Lucey et al. (10) reported no significant associations between hypocalcemia and milk yield. Also, Deluyker et al. ( 3 ) reported no association between milk yield and milk fever. Dohoo and Martin ( 5 ) found no direct effect of milk fever on milk yield, but they speculated that a negative association might have been masked by the positive association found between previous milk yield and the occurrence of milk fever. Probably because of the method used to study the question of milk loss, these studies were not able to show any effect. Because cows with milk fever seem to be higher yielding cows and because the disease occurs so early in lactation, it is difficult to show the milk-reducing effect of the disease. When compared with the yield of the healthy cows, no negative effects as a consequence of milk fever were found; the milk yield just dropped to the level of the healthy cows. If 305-d milk yield is used as a milk measure, cows with milk fever still can yield more than healthy cows, despite having contracted the disease, and no effect is evident. Our method of comparing the milk yield of cows with milk fever to their own yield potential later in lactation, however, enabled us to estimate the milk loss caused by milk fever. Our estimates could still underestimate the true effect of milk fever if the cows had other diseases that caused reduced milk yield more than 8 wk after calving (yield at that time was used as the reference level). Ketosis Ketosis had a significant negative effect on milk yield. The milk-reducing effect started even before the diagnosis of clinical ketosis (Table 3), which agrees with the findings of Lucey et al. (10), who reported that milk yield declined for 2 to 4 wk before diagnosis of ketosis. They estimated the total losses in milk yield associated with ketosis to be 60 to 70 kg, which was less than our estimates. In our study, the milk loss continued for at least 2 wk after diagnosis, and the overall loss during the entire lactation (e.g., in parity 1 and in parity 4 or higher) was and kg, respectively (Table 3). In both of these

5 292 RAJALA ET AL. TABLE 3. Effects of ketosis on milk yield (kilograms) by parity for 21,702 Finnish Ayrshire cows that calved in 1993 and were followed for one lactation. 1 1Milk yield of the cows with ketosis more than 4 wk before disease diagnosis was used as the reference level. 2Period when the test day milk sample was collected with respect to the diagnosis of the disease (BD = before diagnosis; AD = after diagnosis). 3The total loss was calculated assuming a 305-d lactation and ketosis occurring on d 28. Only statistically significant losses within each time period were considered in calculating the total loss. *P **P ***P Parity 1 Parity 2 Parity 3 Parity 4+ Effect 2 Estimate SE Estimate SE Estimate SE Estimate SE d BD 1.2* * d BD 1.7*** *** * *** d AD 3.0*** *** *** *** d AD 1.5** ** *** d AD 1.6** *** 0.8 >42 d AD *** 0.8 Healthy 1.1* * 0.8 Total loss parity groups, the milk-reducing effect started 4 wk prior to the diagnosis. The daily milk loss was greatest within the first 2 wk after the diagnosis, being 3.0, 4.0, 3.3, and 5.3 kg/d for parities 1, 2, 3, and 4 or higher, respectively. In parity 4 or higher, the milk loss continued for the rest of the lactation, which could be an indication that the energy requirements of the cows were not met. The healthy cows in parity 1 and in parity 4 or higher yielded significantly less than the cows that contracted ketosis; healthy cows in parity 1 yielded on average 1.1 kg less milk/d, and cows in parity 4 or higher yielded 1.8 kg less milk/d than ketotic cows in the same parity. This is in agreement with the results of Detilleux et al. (4), who also reported that ketotic cows yielded more milk over the entire lactation than did the healthy cows. They also reported a significant depression in the lactation curve of the ketotic cows in early lactation. TABLE 4. Effects of lameness on milk yield (kilograms) by parity for 21,438 Finnish Ayrshire cows that calved in 1993 and were followed for one lactation. 1 1Milk yield of cows with foot and leg disorders more than 4 wk before the disease diagnosis was used as the reference level. 2Period when the test day milk sample was collected with respect to the diagnosis of the disease (BD = before diagnosis; AD = after diagnosis). 3The total loss was calculated assuming a 305-d lactation and lameness occurring on d 52. Only statistically significant losses within each time period were considered in calculating the total loss. *P **P ***P Parity 1 Parity 2 Parity 3 Parity 4+ Effect 2 Estimate SE Estimate SE Estimate SE Estimate SE d BD d BD 1.5*** ** d AD 1.5*** *** d AD 1.6*** * *** d AD 1.0* * 0.8 >42 d AD 1.1** Healthy ** 0.7 Total loss

6 EFFECTS OF METABOLIC DISEASES ON MILK YIELD 293 Dohoo and Martin (5), however, reported that a case of ketosis appeared to increase yield by approximately 2.5%, and they attributed that increase to the initial therapy and follow-up therapy after the diagnosis. Another possible, and maybe even more likely, explanation could be that cows with ketosis were higher yielding and simply milked more even after contracting ketosis, as was found in our study. Rowlands and Lucey (13) reported an average significant reduction of 6 to 7% in peak yield in lactations in which the cows had ketosis. There was, however, no overall significant difference in 305-d milk yield. All of these findings indicate that cows with ketosis are, in general, higher yielding and that the milk loss often is only temporary. Lameness The lactational incidence risk of lameness (foot and leg disorders) was very low in our data at only 2.1%. Our current data consisted of healthy cows and lame cows that had no other diseases within the 4 wk before and 4 wk after the lameness diagnosis. Thus, we were able to exclude the confounding effect caused by any other diseases occurring close to the lameness diagnosis. We compared the milk yield of cows with foot and leg disorders to their own yield more than 4 wk before the diagnosis. Milk yield of cows in parity 1 began to decline 2 wk before the clinical diagnosis of the disorder, the loss being 1.5 kg/d (Table 4). Within the first 2 wk after the diagnosis, the loss was 1.5 kg/ d; during the following 2 wk, the loss was 1.6 kg/d, and, during the following 2 wk, the loss was 1.0 kg/d. The negative effect continued even longer (i.e., for the rest of the lactation), and the loss was 1.1 kg/d. In parity 2, lameness had a negative effect on milk yield; however, the effect was not significant. The lactational incidence risk of lameness was lowest in parity 2, and a small sample size might partly explain why we were not able to detect significant effects. In parity 3, the loss during the first 2 wk after the diagnosis was 2.0 kg/d ( P < 0.07) and, during the following 2 wk, it was 2.2 kg/d. In parity 4 or higher, the milk-reducing effect began 2 wk before the diagnosis (2.6 kg/d) and continued for 6 wk after the diagnosis; the loss was 2.8, 2.8, and 1.7 kg/d during the three 2-wk periods following the diagnosis. In parity 4 or higher the healthy cows yielded less milk (1.8 kg/d) than did the cows with foot and leg disorders; among younger cows, there was no significant difference. Dohoo and Martin ( 5 ) reported a large positive direct effect of foot and leg disorders on milk yield (expressed as kilograms of milk per day of life); the overall effect represented an increase of approximately 1.6% in milk yield per day of life. Again, this effect could probably be explained by the fact that, in their data, cows with foot and leg disorders were higher yielding cows. Also, Rowlands and Lucey (13) reported that cases of lameness were more common in cows that had higher than average peak milk yields, and Deluyker et al. ( 3 ) reported that limping diagnosed within 49 d after calving coincided with higher daily yield during 1 to 5 d postpartum and higher cumulative yield up to 21 d and 49 to 119 d postpartum, which is in agreement with our observation that lame cows in parity 4 or higher produced 1.8 kg more milk/d than did the healthy cows. Our estimates could be underestimating the true effect of lameness if the cows had some other diseases causing reduced milk yield more than 4 wk before the lameness diagnosis. It should be noted that all of these diseases were recorded by veterinarians. Some minor cases of ketosis and leg and foot disorders might not be recorded if the farmer does not seek veterinary attention for these cows. But, even if some of the cows with these diseases were misclassified as healthy in our study, their proportion in that group was so small that it would not have had a significant effect. In the estimation of milk loss among the diseased cows, however, some overestimation of the milk loss might occur if some minor cases are not included in the data. CONCLUSIONS Milk fever affected milk yield for 4 to 6 wk after calving; the loss varied between 1.1 and 2.9 kg/d, depending on parity and the time elapsed after the diagnosis. Cows contracting milk fever were higher yielding than were healthy cows. Ketosis had a negative effect on milk yield; milk yield began to decline 2 to 4 wk before the diagnosis of ketosis, and the milkreducing effect continued for a varying length of time, depending on parity. The losses were greatest during the 2 wk following the diagnosis (varying from 3.0 to 5.3 kg/d). Also, lameness had a negative effect on milk yield; cows in parity 1 were affected most. ACKNOWLEDGMENTS The study was supported by the Finnish Academy, Walther Ehrström Foundation, Foundation of Veterinary Medicine in Finland (Suomen eläinlääketieteen säätiö) and the Faculty of Veterinary Medicine of Helsinki University (Helsinki, Finland). This research was conducted using the resources of the Cornell Theory Center (Cornell University, Ithaca, NY), which receives major funding from the National

7 294 RAJALA ET AL. Science Foundation (Arlington, VA) and New York State with additional support from the Advanced Research Projects (Arlington, VA), the National Center for Research Resources at the National Institute of Health (Bethesda, MD), IBM Corporation (Armonk, NY), and other members of the Center s Corporate Partnership Program. The work of Charles E. McCulloch was partially supported by the National Science Foundation Grant DMS REFERENCES 1 Bendixen, P. H., B. Vilson, I. Ekesbo, and D. B. Åstrand Disease frequencies in dairy cows in Sweden. III. Parturient paresis. Prev. Vet. Med. 5: Bigras-Poulin, M., A. H. Meek, and S. W. Martin Interrelationships among health problems and milk production from consecutive lactations in selected Ontario Holstein cows. Prev. Vet. Med. 8: Deluyker, H. A., J. M. Gay, L. D. Weaver, and A. S. Azari Change of milk yield with clinical diseases for a high producing dairy herd. J. Dairy Sci. 74: Detilleux, J. C., Y. T. Gröhn, and R. L. Quaas Effects of clinical ketosis on test day milk yields in Finnish Ayrshire cattle. J. Dairy Sci. 77: Dohoo, I. R., and S. W. Martin Disease, production and culling in Holstein-Friesian cows. IV. Effects of disease on production. Prev. Vet. Med. 2: Dohoo, I. R., S. W. Martin, A. H. Meek, and W.C.D. Sandals Disease, production and culling in Holstein-Friesian cows. III. Disease and production as determinants of disease. Prev. Vet. Med. 2: Gröhn, Y. T., H. N. Erb, C. E. McCulloch, and H. S. Saloniemi Epidemiology of metabolic disorders in dairy cattle: association among host characteristics, disease, and production. J. Dairy Sci. 72: Gröhn, Y. T., H. N. Erb, C. E. McCulloch, and H. S. Saloniemi Epidemiology of mammary gland disorders in multiparous Finnish Ayrshire cows. Prev. Vet. Med. 8: Littell, R. C., G. A. Milliken, W. W. Stroup, and R. D. Wolfinger SAS System for Mixed Models. SAS Inst., Inc., Cary, NC. 10 Lucey, S., G. J. Rowlands, and A. Russell Short-term associations between disease and milk yield of dairy cows. J. Dairy Res. 53: Rajala, P. J., and Y. T. Gröhn Disease occurrence and risk factors analysis in Finnish Ayrshire cows. Acta Vet. Scand. 39: Rajala, P. J., and Y. T. Gröhn Effects of dystocia, retained placenta and metritis on milk yield in Finnish Ayrshire cows. J. Dairy Sci. 81: Rowlands, G. J., and S. Lucey Changes in milk yield in dairy cows associated with metabolic and reproductive disease and lameness. Prev. Vet. Med. 4:

The relationship between lameness and milk yield in. Comparison of milk yield in dairy cows with different degrees of lameness

The relationship between lameness and milk yield in. Comparison of milk yield in dairy cows with different degrees of lameness Comparison of milk yield in dairy cows with different degrees of lameness Jorge A. Hernandez, DVM, MPVM, PhD; Eduardo J. Garbarino, DVM, MS; Jan K. Shearer, DVM, MS; Carlos A. Risco, DVM; William W. Thatcher,

More information

Economics of Postpartum Uterine Health

Economics of Postpartum Uterine Health Economics of Postpartum Uterine Health Michael Overton DVM, MPVM University of Georgia, College of Veterinary Medicine 425 River Road Athens, GA 30602-2771 moverton@uga.edu John Fetrow VMD, MBA University

More information

Use of the Transition Cow Index as a Monitor of Herd Health. Health Records would appear to be obvious monitor, but.

Use of the Transition Cow Index as a Monitor of Herd Health. Health Records would appear to be obvious monitor, but. Use of the Transition Cow Index as a Monitor of Herd Health Peter D. Giacomini AgSource Cooperative Services Verona, Wisc. USA Transition Period Period 3 weeks before and after calving Area of increased

More information

Advancing parity is associated with high milk production at the cost of body condition and increased periparturient disorders in dairy herds

Advancing parity is associated with high milk production at the cost of body condition and increased periparturient disorders in dairy herds J. Vet. Sci. (2006),G7(2), 161 166 J O U R N A L O F Veterinary Science Advancing parity is associated with high milk production at the cost of body condition and increased periparturient disorders in

More information

Implementation of a Body Condition Scoring Program in Dairy Herds

Implementation of a Body Condition Scoring Program in Dairy Herds Implementation of a Body Condition Scoring Program in Dairy Herds Penn Conference 1996 James D. Ferguson Associate Professor Center for Animal Health and Productivity University of Pennsylvania, School

More information

Variation of somatic cell count (SCC) of dairy cattle in conditions of Mediterranean region in Croatia

Variation of somatic cell count (SCC) of dairy cattle in conditions of Mediterranean region in Croatia Variation of somatic cell count (SCC) of dairy cattle in conditions of Mediterranean region in Croatia P. Mijić 1, V. Gantner 1, T. Bobić 1 & K. Kuterovac 2 1 Faculty of Agriculture, J.J. Strossmayer University

More information

REDUCED AGE AT FIRST CALVING: EFFECTS ON LIFETIME PRODUCTION, LONGEVITY, AND PROFITABILITY

REDUCED AGE AT FIRST CALVING: EFFECTS ON LIFETIME PRODUCTION, LONGEVITY, AND PROFITABILITY Dairy Day 2004 REDUCED AGE AT FIRST CALVING: EFFECTS ON LIFETIME PRODUCTION, LONGEVITY, AND PROFITABILITY M. J. Meyer 1, R. W. Everett 1, and M. E. Van Amburgh 1 Summary The primary advantages of reducing

More information

Effective transition cow management to maximize Internal Herd Growth. Thomas R. Overton, Ph.D. Department of Animal Science Cornell University

Effective transition cow management to maximize Internal Herd Growth. Thomas R. Overton, Ph.D. Department of Animal Science Cornell University Effective transition cow management to maximize Internal Herd Growth Thomas R. Overton, Ph.D. Department of Animal Science Cornell University Our charge Devise and employ nutritional management strategies

More information

Investigation on Genotype by Environment Interaction for Milk Yield of Holstein Cows in Luxembourg and Tunisia

Investigation on Genotype by Environment Interaction for Milk Yield of Holstein Cows in Luxembourg and Tunisia Investigation on Genotype by Environment Interaction for Milk Yield of Holstein Cows in and H. Hammami 1, 5, C. Croquet 1,2, H. Soyeurt 1,4, S. Vanderick 1, S. Khlij 5, J. Stoll 3 and N. Gengler 1,2 1

More information

Prediction of the herd somatic cell count of the following month using a linear mixed effect model

Prediction of the herd somatic cell count of the following month using a linear mixed effect model J. Dairy Sci. 93 :234 241 doi: 10.3168/jds.2009-2580 American Dairy Science Association, 2010. Prediction of the herd somatic cell count of the following month using a linear mixed effect model J. J. Lievaart,*

More information

MONTHLY HERD SUMMARY REPORT

MONTHLY HERD SUMMARY REPORT MONTHLY HERD SUMMARY REPORT Monthly Herd Summary Report Monthly Herd Summary Report Monthly Herd Summary Report Monthly Herd Summary Report Monthly Herd Summary Report Monthly Herd Summary Report Report

More information

Effect of different dry period lengths on milk production and somatic cell count in subsequent lactations in commercial Dutch dairy herds

Effect of different dry period lengths on milk production and somatic cell count in subsequent lactations in commercial Dutch dairy herds J. Dairy Sci. 96 :2988 3001 http://dx.doi.org/ 10.3168/jds.2012-6297 American Dairy Science Association, 2013. Effect of different dry period lengths on milk production and somatic cell count in subsequent

More information

Impact of Dry Period Length

Impact of Dry Period Length Rick Watters, Paul Fricke, Milo Wiltbank, and Ric Grummer Department of Dairy Science, University of Wisconsin-Madison Perry Clark Department of Dairy Science, University of Wisconsin-River Falls Take-home

More information

DEVELOPMENT OF STANDARD METHODS TO ESTIMATE MANURE PRODUCTION AND NUTRIENT CHARACTERISTICS FROM DAIRY CATTLE

DEVELOPMENT OF STANDARD METHODS TO ESTIMATE MANURE PRODUCTION AND NUTRIENT CHARACTERISTICS FROM DAIRY CATTLE This is not a peer-reviewed article. Pp. 263-268 in the Ninth International Animal, Agricultural and Food Processing Wastes Proceedings of the 12-15 October 2003 Symposium (Research Triangle Park, North

More information

Section 1 : Identification sheet

Section 1 : Identification sheet MINISTRY OF AGRICULTURE, FISHERIES AND FOOD Research and Development 30/09/98 Final Project Report (Not to be used for LINK projects) Date project completed: 1. (a) MAFF Project Code OF0113 Section 1 :

More information

Ketosis measurements in veterinary practice

Ketosis measurements in veterinary practice 2016 Ketosis measurements in veterinary practice J.C. van Schaik Universiteit Utrecht Faculteit Diergeneeskunde 26-8-2016 Index Abstract... 2 Introduction... 3 Material and Methods... 5 Results... 6 Discussion...

More information

SimHerd exercises: answers

SimHerd exercises: answers Jehan Ettema, SimHerd Inc., 22-03-2016 Info: The answers to the questions in the exercises are presented below. The answer can differ from your answers; results differ due to the variation in the stochastic

More information

The Cost of Generic Clinical Mastitis in Dairy Cows as Estimated by Using Dynamic Programming

The Cost of Generic Clinical Mastitis in Dairy Cows as Estimated by Using Dynamic Programming J. Dairy Sci. 91:2205 2214 doi:10.3168/jds.2007-0573 American Dairy Science Association, 2008. The Cost of Generic Clinical Mastitis in Dairy Cows as Estimated by Using Dynamic Programming D. Bar,* 1 L.

More information

Using Cow Behaviour to Predict Disease

Using Cow Behaviour to Predict Disease Using Cow Behaviour to Predict Disease Marina A. G. von Keyserlingk, Katy L. Proudfoot, Lori Vickers and Daniel M. Weary Animal Welfare Program, University of British Columbia, Vancouver BC V6T 1Z6 Email:

More information

The value of health data from dairy farmers in the United States

The value of health data from dairy farmers in the United States Clay et al. The value of health data from dairy farmers in the United States J.S. Clay 1, K.L. Parker Gaddis 2 and C. Maltecca 2 1 Dairy Records Management Systems, Raleigh, NC 27603, USA 2 Department

More information

Management of Heat Stress to Improve Fertility in Dairy Cows in Israel

Management of Heat Stress to Improve Fertility in Dairy Cows in Israel 5 10 15 Management of Heat Stress to Improve Fertility in Dairy Cows in Israel Israel Flamenbaum ¹ and Nadav Galon ² ¹ Advanced Cow Cooling Systems Co., Tel Aviv, Israel ² - Hachaklait Veterinary Services

More information

Dairy Production and Management Benchmarks

Dairy Production and Management Benchmarks Cooperative Extension Service The University of Georgia College of Agricultural and Environmental Sciences Dairy Production and Management Benchmarks Table of Contents Introduction... 3 Methods... 3 Rolling

More information

http://researchoutput.csu.edu.au This is the Author s version of the paper published as: Author: J. S. o. A. Lievaart, C. S. U. W. W. A. Veterinary Sciences, F. o. V. M. U. o. U. U. t. N. Kremer W.D. Department

More information

Management Tools to Increase Dairy Cow Feed Efficiency. V.E. Cabrera and A. Kalantari University of Wisconsin-Madison Dairy Science

Management Tools to Increase Dairy Cow Feed Efficiency. V.E. Cabrera and A. Kalantari University of Wisconsin-Madison Dairy Science Management Tools to Increase Dairy Cow Feed Efficiency V.E. Cabrera and A. Kalantari University of Wisconsin-Madison Dairy Science Wisconsin Feed Efficiency Workshop 2015 Feeding Heifers Reproduction

More information

Effect of Metabolic Diseases on Dry Matter Consumption and Production Parameters

Effect of Metabolic Diseases on Dry Matter Consumption and Production Parameters Effect of Metabolic Diseases on Dry Matter Consumption and Production Parameters Richard L. Wallace, Gene C. McCoy, Thomas R. Overton, and Jimmy H. Clark TAKE-HOME MESSAGES Postpartum metabolic diseases

More information

COW PRODUCTION MONTHLY REPORT

COW PRODUCTION MONTHLY REPORT COW PRODUCTION MONTHLY REPORT Report objectives to provide individual cow identification, age, calving and lactation number information; to provide individual cow current test day milk weights and milk

More information

Big Data, Science and Cow Improvement: The Power of Information!

Big Data, Science and Cow Improvement: The Power of Information! Big Data, Science and Cow Improvement: The Power of Information! Brian Van Doormaal, Canadian Dairy Network (CDN) Building a Sustainable Dairy Industry, DFC Symposium November 7-8, 2017, Ottawa Our Product

More information

PERFORMANCE OF DAIRY CATTLE UNDER TWO DIFFERENT FEEDING SYSTEMS, AS PRACTICED IN KIAMBU AND NYANDARUA DISTRICTS OF CENTRAL KENYA

PERFORMANCE OF DAIRY CATTLE UNDER TWO DIFFERENT FEEDING SYSTEMS, AS PRACTICED IN KIAMBU AND NYANDARUA DISTRICTS OF CENTRAL KENYA PERFORMANCE OF DAIRY CATTLE UNDER TWO DIFFERENT FEEDING SYSTEMS, AS PRACTICED IN KIAMBU AND NYANDARUA DISTRICTS OF CENTRAL KENYA P.N. MBUGUA, C.K. GACHUIRI, R.G. WAHOME, M.M. WANYOIKE, A. ABATE Department

More information

Figure 1. Dry matter intake, milk yield and live weight changes in a cow during her lactation cycle

Figure 1. Dry matter intake, milk yield and live weight changes in a cow during her lactation cycle Welcome to the sixth edition (Sep 2014) of the ADN News. This newsletter discusses the very important topic of persistency of milk production during the cow s lactation cycle and the dramatic adverse impact

More information

Grouping Strategies for Feeding Lactating Dairy Cattle. V.E. Cabrera

Grouping Strategies for Feeding Lactating Dairy Cattle. V.E. Cabrera Grouping Strategies for Feeding Lactating Dairy Cattle V.E. Cabrera Online Web-Based Application at http://dairymgt.info Tools Feeding Dairy farmers might overfeed to a large proportion of animals in order

More information

C ASE STUDY: Characterization

C ASE STUDY: Characterization The Professional Animal Scientist 30 (2014):109 113 2014 American Registry of Professional Animal Scientists C ASE STUDY: Characterization of lying behavior in dairy cows transitioning from a freestall

More information

R elationships between age at

R elationships between age at The Professional Animal Scientist 29 (2013):1 9 2013 American Registry of Professional Animal Scientists R elationships between age at first calving; herd management criteria; and lifetime milk, fat, and

More information

Polish Federation of Cattle Breeders and Dairy Farmers, Zurawia 22, Warsaw, Poland 3

Polish Federation of Cattle Breeders and Dairy Farmers, Zurawia 22, Warsaw, Poland 3 Kowalski et al. Novel model of monitoring of subclinical ketosis in dairy herds in Poland based on monthly milk recording and estimation of ketone bodies in milk by FTIR spectroscopy technology Z. Kowalski

More information

Valacta contributes to the sustainable development and prosperity of the dairy sector through knowledge transfer, information management and analysis

Valacta contributes to the sustainable development and prosperity of the dairy sector through knowledge transfer, information management and analysis Valacta contributes to the sustainable development and prosperity of the dairy sector through knowledge transfer, information management and analysis services Client Satisfaction 95% 5,200 clients 300

More information

Factors Affecting Fertility of Dairy Cows in Israel

Factors Affecting Fertility of Dairy Cows in Israel Journal of Reproduction and Development, Vol. 56, Suppl, 2010 Factors Affecting Fertility of Dairy Cows in Israel Nadav GALON 1), Yoel ZERON 2) and Ephraim EZRA 3) 1) Hachaklait Veterinary Services Ltd,

More information

Locomotion Scoring Your Cows: Use and Interpretation

Locomotion Scoring Your Cows: Use and Interpretation Locomotion Scoring Your Cows: Use and Interpretation P.H. Robinson and S.T. Juarez Department of Animal Science University of California, Davis, CA 95616-8521 Introduction Lameness of dairy cattle is an

More information

EXTENDED LACTATION STRATEGIES

EXTENDED LACTATION STRATEGIES 23.04.2015 EXTENDED LACTATION STRATEGIES Charlotte Gaillard, Troels Kristensen, Jakob Sehested 2 The lactation curve is plastic Persistency: slope of decline in milk yield after the peak (high persistency

More information

Measurement error variance of testday observations from automatic milking systems

Measurement error variance of testday observations from automatic milking systems Measurement error variance of testday observations from automatic milking systems Pitkänen, T., Mäntysaari, E. A., Nielsen, U. S., Aamand, G. P., Madsen, P. and Lidauer, M. H. Nordisk Avlsværdivurdering

More information

Designing Heifer Systems That Work on Your Farm

Designing Heifer Systems That Work on Your Farm Designing Heifer Systems That Work on Your Farm Michael E. Van Amburgh and Thomas R. Overton Department of Animal Science, Cornell University, Ithaca, NY 14853 Email: tro2@cornell.edu Take Home Messages

More information

Improving fertility through management and genetics.

Improving fertility through management and genetics. Improving fertility through management and genetics., Director of Research, Holstein USA Introduction It is a great pleasure to be giving this talk to an international group of enthusiast Holstein breeders

More information

56 th Annual Meeting of the Euopean Association for Animal Production Uppsala (Sweden), June ,

56 th Annual Meeting of the Euopean Association for Animal Production Uppsala (Sweden), June , 56 th Annual Meeting of the Euopean Association for Animal Production Uppsala (Sweden), June 5-8 2005, Session: V1 Nutrition and management strategies to improve resource use in livestock systems Effect

More information

Using lactation curves as a tool for breeding, nutrition and health management decisions in pasture-based dairy systems.

Using lactation curves as a tool for breeding, nutrition and health management decisions in pasture-based dairy systems. Using lactation curves as a tool for breeding, nutrition and health management decisions in pasture-based dairy systems. S.A. Adediran 1,A.E.O. Malau-Aduli 1, J. R. Roche 1,2, and D.J. Donaghy 1,2 1 School

More information

Herd Navigator TM focus on the right cow, at the right time, with the right treatment. Available for VMS & ALPRO Parlour

Herd Navigator TM focus on the right cow, at the right time, with the right treatment. Available for VMS & ALPRO Parlour Herd Navigator TM focus on the right cow, at the right time, with the right treatment Available for & ALPRO Parlour Herd Navigator has achieved amazing results 1 in terms of improving productivity on dairy

More information

Once-a-day Milking in Late Lactation

Once-a-day Milking in Late Lactation Once-a-day Milking in Late Lactation Jane Kay, DairyNZ Once-a-day (OAD) milking has been used as a management strategy for many years in New Zealand. Current records indicate that 4% of herds are milked

More information

Ph2.10 (poster) Calving season affects reproductive performance of high yielding but not low yielding Jersey cows

Ph2.10 (poster) Calving season affects reproductive performance of high yielding but not low yielding Jersey cows Ph2.10 (poster) esoydan@omu.edu.tr EAAP Annual Meeting, Uppsala, Sweden, 5-8 June 2005 affects reproductive performance of high yielding but not low yielding Jersey cows E. Soydan 1*, E. Sirin 1, Z. Ulutas

More information

Zoetis Expands Genetics Portfolio With Calf Wellness Traits in Clarifide Plus

Zoetis Expands Genetics Portfolio With Calf Wellness Traits in Clarifide Plus FOR IMMEDIATE RELEASE March 1, 2018 Media Contacts: Cheryl Marti Kristina Hopkins Zoetis Bader Rutter 608-206-0635 262-938-5577 cheryl.f.marti@zoetis.com khopkins@bader-rutter.com Zoetis Expands Genetics

More information

ESTIMATION OF BREEDING VALUES OF SAHIWAL CATTLE USING TEST DAY MILK YIELDS

ESTIMATION OF BREEDING VALUES OF SAHIWAL CATTLE USING TEST DAY MILK YIELDS ESTIMATION OF BREEDING VALUES OF SAHIWAL CATTLE USING TEST DAY MILK YIELDS M. S. KHAN, G. BILAL, I. R. BAJWA, Z. REHMAN 1 AND S. AHMAD 2 Department of Animal Breeding & Genetics, University of Agriculture,

More information

Proc. Assoc. Advmt. Anim. Breed. Genet. 20:57-61

Proc. Assoc. Advmt. Anim. Breed. Genet. 20:57-61 CHARACTERISTICS OF EXTENDED LACTATION AND PERSISTENCY IN AUSTRALIAN DAIRY COWS M. Abdelsayed, P.C. Thomson, and H.W. Raadsma ReproGen Animal Bioscience Group, Faculty of Veterinary Science, University

More information

Animal welfare, etológia és tartástechnológia

Animal welfare, etológia és tartástechnológia Animal welfare, etológia és tartástechnológia Animal welfare, ethology and housing systems Volume 5 Issue 4 Különszám Gödöllı 2009 103 DEVELOPMENT OF A SENSOR-BASED MONITORING SYSTEM FOR THE ANALYSIS OF

More information

Dietary Grouping Strategies to Improve Profitability on Dairy Farms!

Dietary Grouping Strategies to Improve Profitability on Dairy Farms! XIX Congreso ANEMBE Oviedo, 25-27 June 2014, Oviedo, Spain! Improving cost-efficiency and profitability! Dietary Grouping Strategies to Improve Profitability on Dairy Farms! V.E. Cabrera & A. Kalantari!

More information

EVALUATING SEMEN FERTILITY OF ARTIFICIAL INSEMINATION SIRES. R. W. EVERETT, USA Department of Animal Science Cornell University Ithaca, NY

EVALUATING SEMEN FERTILITY OF ARTIFICIAL INSEMINATION SIRES. R. W. EVERETT, USA Department of Animal Science Cornell University Ithaca, NY EVALUATING SEMEN FERTILITY OF ARTIFICIAL INSEMINATION SIRES R. W. EVERETT, USA Department of Animal Science Cornell University Ithaca, NY J. F. TAYLOR, AUSTRALIA Department of Tropical Veterinary Medicine

More information

Effects of Early and Late Breeding of Heifers on Multiple Lactation Performance of Dairy Cows! 1

Effects of Early and Late Breeding of Heifers on Multiple Lactation Performance of Dairy Cows! 1 Effects of Early and Late Breeding of Heifers on Multiple Lactation Performance of Dairy Cows! 1 C. Y. LIN, A. J. McALLISTER, T. R. BATRA, and A. J. LEE Animal Research Centre Agriculture Canada Ontario

More information

THE EFFECTS OF CONDITION SCORE ON THE PERFORMANCE OF EARLY LACTATION HOLSTEIN COWS

THE EFFECTS OF CONDITION SCORE ON THE PERFORMANCE OF EARLY LACTATION HOLSTEIN COWS THE EFFECTS OF CONDITION SCORE ON THE PERFORMANCE OF EARLY LACTATION HOLSTEIN COWS Mike McCormick, Associate Professor, Southeast Research Station Dennis French, Professor, Veterinary Science Department

More information

Use of daily robotic progesterone data for improving fertility traits in Finnish Ayrshire

Use of daily robotic progesterone data for improving fertility traits in Finnish Ayrshire Use of daily robotic progesterone data for improving fertility traits in Finnish Ayrshire J. Häggman 1, J.M. Christensen 2 and J. Juga 2 1 Department of Agricultural Sciences, University of Helsinki, FI-00014,

More information

GENETIC AND ENVIRONMENTAL FACTORS INFLUENCING PERSISTENCY OF MILK PRODUCTION IN KARAN FRIES CATTLE*

GENETIC AND ENVIRONMENTAL FACTORS INFLUENCING PERSISTENCY OF MILK PRODUCTION IN KARAN FRIES CATTLE* Indian J. Anim. Res., 40 (2): 95-100, 2006 GENETIC AND ENVIRONMENTAL FACTORS INFLUENCING PERSISTENCY OF MILK PRODUCTION IN KARAN FRIES CATTLE* Amit Kumar and Avtar Singh Dairy Cattle Breeding Division,

More information

Strategies to Improve Economic Efficiency of the Dairy

Strategies to Improve Economic Efficiency of the Dairy Strategies to Improve Economic Efficiency of the Dairy Victor E. Cabrera and Afshin S. Kalantari 1675 Observatory Dr., University of Wisconsin Madison, Department of Dairy Science, Madison, WI 53706 Email:

More information

Dairy Reproduction Benchmarks. J.W. Smith, W.D. Gilson, L.O. Ely and W.M. Graves Animal and Dairy Science Department

Dairy Reproduction Benchmarks. J.W. Smith, W.D. Gilson, L.O. Ely and W.M. Graves Animal and Dairy Science Department Dairy Reproduction Benchmarks J.W. Smith, W.D. Gilson, L.O. Ely and W.M. Graves Animal and Dairy Science Department Dairy Reproduction Benchmarks Table of Contents Introduction...3 Methods...3 Figure 1:

More information

STUDY OF SOME PERFORMANCE TRAITS IN SAHIWAL COWS DURING DIFFERENT PERIODS

STUDY OF SOME PERFORMANCE TRAITS IN SAHIWAL COWS DURING DIFFERENT PERIODS STUDY OF SOME PERFORMANCE TRAITS IN SAHIWAL COWS DURING DIFFERENT PERIODS A. H. ZAFAR, M. AHMAD 1 AND S. U. REHMAN Livestock Production Research Institute, Bahadurngar, Okara; 1 Buffalo Research Institute,

More information

Key Performance Indicators for the UK national dairy herd

Key Performance Indicators for the UK national dairy herd Key Performance Indicators for the UK national dairy herd A study of herd performance in 500 Holstein/Friesian herds for the year ending 31 st August 2017 Dr. James Hanks & Dr. Mohamad Kossaibati November,

More information

THE USE OF BOVINE SOMATOTROPIN (BST) IN DAIRY CATTLE

THE USE OF BOVINE SOMATOTROPIN (BST) IN DAIRY CATTLE THE USE OF BOVINE SOMATOTROPIN (BST) IN DAIRY CATTLE Jorge Estrada and J. E. Shirley General Information We all have heard about the use of BST in lactating dairy cattle during the last 6 to 8 years, but

More information

NTM. Breeding for what truly matters. The NTM breeding goal is healthy, fertile, high producing cows the invisible cow. Elisabeth

NTM. Breeding for what truly matters. The NTM breeding goal is healthy, fertile, high producing cows the invisible cow. Elisabeth NTM Breeding for what truly matters The NTM breeding goal is healthy, fertile, high producing cows the invisible cow. Elisabeth 1 Contents Nordic Total Merit NTM a powerful tool for dairy farmers 3 How

More information

Identifying Transition Cows at Risk and How Best to Manage Them

Identifying Transition Cows at Risk and How Best to Manage Them 45 Identifying Transition Cows at Risk and How Best to Manage Them M.A.G. von Keyserlingk 1 and D.M. Weary Animal Welfare Program University of British Columbia,Vancouver, BC, Canada Take Home Messages

More information

Association of Cow and Quarter Level Factors at Dry Off and New Intramammary Infections in the Dry Period

Association of Cow and Quarter Level Factors at Dry Off and New Intramammary Infections in the Dry Period Animal Industry Report AS 650 ASL R1912 2004 Association of Cow and Quarter Level Factors at Dry Off and New Intramammary Infections in the Dry Period Randy Dingwell University of Guelph Ken Leslie University

More information

Genetic Analysis of Cow Survival in the Israeli Dairy Cattle Population

Genetic Analysis of Cow Survival in the Israeli Dairy Cattle Population Genetic Analysis of Cow Survival in the Israeli Dairy Cattle Population Petek Settar 1 and Joel I. Weller Institute of Animal Sciences A. R. O., The Volcani Center, Bet Dagan 50250, Israel Abstract The

More information

1.1 Present improvement of breeding values for milking speed

1.1 Present improvement of breeding values for milking speed Use of data from electronic milk meters and perspectives in use of other objective measures Anders Fogh 1, Uffe Lauritsen 2 and Gert Pedersen Aamand 1 1 Knowledge Center for Agriculture, Agro Food Park

More information

Transition period: Accommodating Group Changes and Cow Need

Transition period: Accommodating Group Changes and Cow Need Transition period: Accommodating Group Changes and Cow Need Ricardo C. Chebel 1, Paula R. B. Silva 1,2, Karen Lobeck- Lutcherhand 2, Marcia Endres 2, Daniela Liboreiro 2 1 University of Florida 2 University

More information

Feeding Concentrate in Early Lactation Based on Rumination Time

Feeding Concentrate in Early Lactation Based on Rumination Time Feeding Concentrate in Early Lactation Based on Rumination Time EAAP, August 28, Copenhagen 2014 M. V. Byskov 1, M. R. Weisbjerg 2, B. Markussen 3, O. Aaes 1 & P. Nørgaard 4 1) Knowledge Centre for Agriculture,

More information

Value of cooperative phenotypic databases in the genomics era

Value of cooperative phenotypic databases in the genomics era Value of cooperative phenotypic databases in the genomics era Albert De Vries Department of Animal Sciences University of Florida Gainesville, FL devries@ufl.edu Future of Phenotyping Council on Dairy

More information

Enhancing the Data Pipeline for Novel Traits in the Genomic Era: From farms to DHI to evaluation centres Dr. Filippo Miglior

Enhancing the Data Pipeline for Novel Traits in the Genomic Era: From farms to DHI to evaluation centres Dr. Filippo Miglior Enhancing the Data Pipeline for Novel Traits in the Genomic Era: From farms to DHI to evaluation centres Dr. Filippo Miglior Chief Research and Strategic Development Canadian Dairy Network Adjunct Professor,

More information

Multiplicative Factors for Estimating Daily Milk and Component Yields from Single a.m. or p.m. Tests

Multiplicative Factors for Estimating Daily Milk and Component Yields from Single a.m. or p.m. Tests Multiplicative Factors for Estimating Daily Milk and Component Yields from Single a.m. or p.m. Tests by C. Lee, E.J. Pollak, R. W. Everett, Department of Animal Science Cornell University, Ithaca, NY 14853

More information

A SELECTION INDEX FOR ONTARIO DAIRY ORGANIC FARMS

A SELECTION INDEX FOR ONTARIO DAIRY ORGANIC FARMS A SELECTION INDEX FOR ONTARIO DAIRY ORGANIC FARMS Paola Rozzi 1 and Filippo Miglior 2,3 1 OntarBio Organic Farmers' Co-operative, 2, 3 Canadian Dairy Network Guelph, ON, Canada 56 th Annual EAAP Meeting,

More information

Claw Disease Incidence as a New Trait in the Breeding Goal for the Czech Holstein Population

Claw Disease Incidence as a New Trait in the Breeding Goal for the Czech Holstein Population ORIGINAL SCIENTIFIC PAPER 235 Claw Disease Incidence as a New Trait in the Breeding Goal for the Czech Holstein Population Zuzana KRUPOVÁ ( ) Josef PŘIBYL Emil KRUPA Marie WOLFOVÁ Summary The aim of the

More information

Impacts of compact calvings and once-a-day milking in grassland based systems.

Impacts of compact calvings and once-a-day milking in grassland based systems. Impacts of compact calvings and once-a-day milking in grassland based systems. V. BROCARD (1), B. PORTIER (2), J.Y. PORHIEL (3) and C. LOPEZ (4) (1) Institut de l'elevage, BP 85225, 35652 Le Rheu Cedex,

More information

Grouping Strategies to Improve Feed Efficiency

Grouping Strategies to Improve Feed Efficiency Grouping Strategies to Improve Feed Efficiency V.E. Cabrera University of Wisconsin-Madison Dairy Science 26th DISCOVER Conference on Food Animal Agriculture: Dairy Feed Efficiency. September 23-26, 2013

More information

Monitoring Transition Programs

Monitoring Transition Programs Monitoring Transition Programs Copyright 2015, John Fetrow John Fetrow VMD, MBA, DSc (hon) Professor of Dairy Production Medicine College of Veterinary Medicine, University of Minnesota Purpose of monitoring

More information

Procedures for estimation of genetic persistency indices for milk production for the South African dairy industry

Procedures for estimation of genetic persistency indices for milk production for the South African dairy industry 224 Procedures for estimation of genetic persistency indices for milk production for the South African dairy industry B.E. Mostert #, R.R. van der Westhuizen and H.E. Theron ARC-Animal Production Institute,

More information

Ukraine. Vladimir Shablia, PhD. Institute of Animal Science of National Academy of Agrarian Sciences of Ukraine ( Kharkov )

Ukraine. Vladimir Shablia, PhD. Institute of Animal Science of National Academy of Agrarian Sciences of Ukraine ( Kharkov ) Implementation of Developments of Institute of Animal Science in Dairy Cattle Breeding in Ukraine Vladimir Shablia, PhD Institute of Animal Science of National Academy of Agrarian Sciences of Ukraine (

More information

Edinburgh Research Explorer

Edinburgh Research Explorer Edinburgh Research Explorer Genetic parameters of growth in dairy cattle and associations between growth and health traits Citation for published version: Brotherstone, S, Coffey, MP & Banos, G 2007, 'Genetic

More information

Effect of Calving Interval on Milk Yield and Quality Evolution during Lactation in Dairy Cows

Effect of Calving Interval on Milk Yield and Quality Evolution during Lactation in Dairy Cows Effect of Interval on Milk Yield and Quality Evolution during Lactation in Dairy Cows Simona Baul 1*, Ludovic-Toma Cziszter 1, Stelian Acatincai 1, Traian Cismas 1,2, Silvia Erina 1, Dinu Gavojdian 3,

More information

Economic Impact of Bull Choices... A.I. Or Otherwise

Economic Impact of Bull Choices... A.I. Or Otherwise Economic Impact of Bull Choices... A.I. Or Otherwise By Dr. Ben McDaniel Animal Science Department North Carolina State University P.O. Box 7621 Raleigh, NC 27695-7621 919-515-4023 fax 919-515-7780 Email:

More information

Figures and tables to IMPRO final report

Figures and tables to IMPRO final report Figures and tables to IMPRO final report 1 WP2 Figure 1. Location of farms in France, Spain, Germany and Sweden. Table 1. Some characteristics of the visited organic dairy farms Country Total agricultural

More information

Making decisions about new technologies on the dairy

Making decisions about new technologies on the dairy Making decisions about new technologies on the dairy Bewildering number of choices/potential decisions in all aspects of managing a dairy Thomas R. Overton, Ph.D. Professor of Dairy Management Director,

More information

Objectives. Economic Comparison of Conventional vs. Intensive Heifer Rearing Systems. Problems with the Historical Approach to Rearing Calves

Objectives. Economic Comparison of Conventional vs. Intensive Heifer Rearing Systems. Problems with the Historical Approach to Rearing Calves Economic Comparison of Conventional vs. Intensive Heifer Rearing Systems Objectives To evaluate the economic costs and opportunities of conventional vs. intensive heifer rearing systems What are the additional

More information

Sickness behavior in lactating dairy cows 1

Sickness behavior in lactating dairy cows 1 Sickness behavior in lactating dairy cows 1 Marina A. G. von Keyserlingk and Daniel. M. Weary Animal Welfare Program, Faculty of Land and Food Systems, University of British Columbia, Vancouver, Canada,

More information

J. Dairy Sci. 95 : /jds American Dairy Science Association, 2012.

J. Dairy Sci. 95 : /jds American Dairy Science Association, 2012. J. Dairy Sci. 95 :4683 4698 http://dx.doi.org/ 10.3168/jds.2011-5214 American Dairy Science Association, 2012. A simple formulation and solution to the replacement problem: A practical tool to assess the

More information

Estrous synchronization programs for the dairy herd

Estrous synchronization programs for the dairy herd College of Agricultural Sciences Cooperative Extension Estrous synchronization programs for the dairy herd Michael L. O Connor Department of Dairy and Animal Science The Pennsylvania State University 324

More information

KETOSIS SUBCLINICAL MASTITIS HEAT. Proactive herd management

KETOSIS SUBCLINICAL MASTITIS HEAT. Proactive herd management KETOSIS SUBCLINICAL MASTITIS HEAT Proactive herd management Peace of mind Herd Navigator shows you the way to improve herd performance and profitability, empowering you to stay competitive as a professional

More information

Smart farming in dairy cattle: application of RumiWatch noseband sensors for monitoring of calving events in dairy cows

Smart farming in dairy cattle: application of RumiWatch noseband sensors for monitoring of calving events in dairy cows Eidgenössisches Departement für Wirtschaft, Bildung und Forschung WBF Agroscope Smart farming in dairy cattle: application of RumiWatch noseband sensors for monitoring of calving events in dairy cows Nils

More information

Opportunities with Low Profile Cross Ventilated Freestall Facilities

Opportunities with Low Profile Cross Ventilated Freestall Facilities Opportunities with Low Profile Cross Ventilated Freestall Facilities J. F. Smith, J. P. Harner, B. J. Bradford, and M. W. Overton Summary Low profile cross ventilated freestall buildings are one option

More information

PHENOTYPIC CORRELATION BETWEEN COUPLE OF MILK PRODUCTION TRAITS IN ROMANIAN SPOTTED BREED DAIRY HEIFERS FROM S.C. AGROSEM S.A. PIŞCHIA, TIMIŞ COUNTY

PHENOTYPIC CORRELATION BETWEEN COUPLE OF MILK PRODUCTION TRAITS IN ROMANIAN SPOTTED BREED DAIRY HEIFERS FROM S.C. AGROSEM S.A. PIŞCHIA, TIMIŞ COUNTY Lucrări ştiinţifice Zootehnie şi Biotehnologii, vol. 42 (2) (9), Timişoara PHENOTYPIC CORRELATION BETWEEN COUPLE OF MILK PRODUCTION TRAITS IN ROMANIAN SPOTTED BREED DAIRY HEIFERS FROM S.C. AGROSEM S.A.

More information

Aggressive Management Strategies for Improving Reproductive Efficiency

Aggressive Management Strategies for Improving Reproductive Efficiency The Babcock Institute University of Wisconsin Dairy Updates Aggressive Management Strategies for Improving Reproductive Efficiency Reproduction and Genetics No. 604 Author: Dr. Paul M. Fricke 1 Take home

More information

Metabolic Disorders. Amin Ahmadzadeh Department of Animal and Veterinary Science University of Idaho. Acquired Metabolic Disorder

Metabolic Disorders. Amin Ahmadzadeh Department of Animal and Veterinary Science University of Idaho. Acquired Metabolic Disorder Metabolic Disorders Amin Ahmadzadeh Department of Animal and Veterinary Science University of Idaho Sources: Dairy Cattle Science, 1st edition. Editor Tyler Slides courtesy of Dr. H.D. Tyler, Iowa State

More information

Dairy herd batch calving

Dairy herd batch calving Queensland the Smart State Dairy herd batch calving Findings from the Sustainable dairy farm systems for profit project M5 Project Information Series - Studies on Mutdapilly Research Station and subtropical

More information

Effects of Prepartum Supplementation of a Rumen Fermentation Enhancer on Subsequent Beef Cow Performance

Effects of Prepartum Supplementation of a Rumen Fermentation Enhancer on Subsequent Beef Cow Performance Effects of Prepartum Supplementation of a Rumen Fermentation Enhancer on Subsequent Beef Cow Performance D. D. Henry 1, F. M. Ciriaco 1, D. Demeterco 2, V. R. G. Mercadante 1, P. L. P. Fontes 1, T. M.

More information

ABSTRACT. ( Key words: test day animal model, tropics, autocorrelation,

ABSTRACT. ( Key words: test day animal model, tropics, autocorrelation, Application of an Autoregressive Process to Estimate Genetic Parameters and Breeding Values for Daily Milk Yield in a Tropical Herd of Lucerna Cattle and in United States Holstein Herds J.G.V. CARVALHEIRA,*

More information

ON-FARM RECORDING OF NOVEL TRAITS GENETIC PARAMETERS AND RECOMMENDATIONS

ON-FARM RECORDING OF NOVEL TRAITS GENETIC PARAMETERS AND RECOMMENDATIONS ICAR 2016 24-28 October 2016, Puerto Varas, Chile ON-FARM RECORDING OF NOVEL TRAITS GENETIC PARAMETERS AND RECOMMENDATIONS K. Zottl 1, A. Koeck 2, B. Fuerst-Waltl 3, C. Pfeiffer 3, F. Steininger 2, L.

More information

She is weaned! Now what? Fernando Soberon, PhD Technical Service Manager Shur-Gain U.S.A.

She is weaned! Now what? Fernando Soberon, PhD Technical Service Manager Shur-Gain U.S.A. She is weaned! Now what? Fernando Soberon, PhD Technical Service Manager Shur-Gain U.S.A. Where did I come from? 2 3 4 5 2.3 services per conception $40.00 per straw of semen 50% female pregnancies 6 4.6

More information